• Journal of the Korean Society of Industry Convergence
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• v.18 no.1
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• pp.1-9
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• 2015

This research dealt with a two-degree-of-freedom controller which was used for 2-dimensional force generator based on an linear motor. The gain margin of the controller may be reduced when the time constant is near to the sampling time of a discrete controller. In case of low gain controller, it cannot satisfy the control performance. A two-degree-of-freedom controller based on PI-control was proposed. It can manage performance and stability respectively. It also had a kind of a feed-forward control. This scheme can not only lessen gain of conventional PI controller in order to stability but also obtain high tracking performance.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.307-313
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• 2021

In this study, the comparative analysis, among the design standard value of distribution power, the calculated value from the measurement data of strand and the empirical data of the distribution line itself, have been performed for the elastic coefficients and linear expansion coefficients of distribution line conductors. The empirical values of elastic coefficients were lower about 10.6%(892kgf/mm²) than those of the design standard value of the distribution power and there were a little difference between the empirical values of linear expansion coefficients and the design standard value of the distribution power. From the above results, it could be concluded that the empirical values of conductor characteristics should be used in the dip design and installation of distribution line.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1319-1330
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• 2009

In [2] A.Hadjidimos proposed the generalized accelerated over-relaxation (GAOR) methods which generalize the basic iterative method for the solution of linear systems. In this paper we consider the convergence of the two parallel accelerated generalized AOR iterative methods and obtain some convergence theorems for the case when the coefficient matrix A is a block diagonally dominant matrix or a generalized block diagonally dominant matrix.

• Bulletin of the Korean Mathematical Society
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• v.61 no.4
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• pp.917-932
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• 2024

In this paper, we deal with the Euler-Maruyama (EM) scheme for stochastic differential equations driven by G-Brownian motion (G-SDEs). Under the linear growth and the local Lipschitz conditions, the strong convergence as well as the rate of convergence of the EM numerical solution to the exact solution for G-SDEs are established.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.169.3-169
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• 2001

This paper introduces a new approach to analysis of error convergence for a class of iterative learning control systems. First, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established in the form of T-S fuzzy model. We analysis the error convergence in the sense of induced 2 L -norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative learning controller design problem to guarantee the error convergence can be reduced to linear matrix inequality problems. In comparison with others, our learning algorithm ...

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.640-644
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• 2010

When we talk with hands-free in a car or noisy lobby, the performance of the echo canceller degrade because background noise added to echo caused by the distance from mouth to microphone is relatively long. It gives a reason for necessity of noise-robust and high convergence speed adaptive algorithm. And if acoustic echo canceller operated not perfectly, residual signal going through the echo canceller to far-end speaker remains residual echo, which degrade quality of talk. To solve this problem, post-processing needed to remove residual echo ones more. In this paper, we propose a new acoustic echo canceller, which has noise robust and high convergence speed, linked with linear predictor as a post-processor. By computer simulation, it is confirmed that the proposed algorithm shows better performance from acoustic interference cancellation (AIC) viewpoint.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.71-77
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• 1995

In this paper are proposed robust iterative learning control(ILC) algorithms for both linear continuous time-invariant system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.295-304
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• 2003

In this paper, we proposed a hardware-oriented Genetic Algorithm Processor(GAP) based on subpopulation architecture for high-performance convergence and reducing computation time. The proposed architecture was applied to enhancing population diversity for correspondence to premature convergence. In addition, the crossover operator selection and linear ranking subpop selection were newly employed for efficient exploration. As stochastic search space selection through linear ranking and suitable genetic operator selection with respect to the convergence state of each subpopulation was used, the elapsed time of searching optimal solution was shortened. In the experiments, the computation speed was increased by over $10\%$ compared to survival-based GA and Modified-tournament GA. Especially, increased by over $20\%$ in the multi-modal function. The proposed Subpop GA processor was implemented on FPGA device APEX EP20K600EBC652-3 of AGENT 2000 design kit.